refactor: update gemini params

apps/setting/models_provider/impl/gemini_model_provider/model/llm.py

@@ -6,11 +6,18 @@
 @Author  ：Brian Yang
 @Date    ：5/13/24 7:40 AM 
 """
-from typing import List, Dict
+from typing import List, Dict, Optional, Sequence, Union, Any, Iterator, cast
 
+from google.ai.generativelanguage_v1 import GenerateContentResponse
+from google.generativeai.responder import ToolDict
+from google.generativeai.types import FunctionDeclarationType, SafetySettingDict
+from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.messages import BaseMessage, get_buffer_string
+from langchain_core.outputs import ChatGenerationChunk
 from langchain_google_genai import ChatGoogleGenerativeAI
-
+from langchain_google_genai._function_utils import _ToolConfigDict
+from langchain_google_genai.chat_models import _chat_with_retry, _response_to_result
+from google.generativeai.types import Tool as GoogleTool
 from common.config.tokenizer_manage_config import TokenizerManage
 from setting.models_provider.base_model_provider import MaxKBBaseModel
 
@@ -36,10 +43,49 @@ class GeminiChatModel(MaxKBBaseModel, ChatGoogleGenerativeAI):
         )
         return gemini_chat
 
+    def get_last_generation_info(self) -> Optional[Dict[str, Any]]:
+        return self.__dict__.get('_last_generation_info')
+
     def get_num_tokens_from_messages(self, messages: List[BaseMessage]) -> int:
-        tokenizer = TokenizerManage.get_tokenizer()
+        return self.get_last_generation_info().get('input_tokens', 0)
-        return sum([len(tokenizer.encode(get_buffer_string([m]))) for m in messages])
 
     def get_num_tokens(self, text: str) -> int:
-        tokenizer = TokenizerManage.get_tokenizer()
+        return self.get_last_generation_info().get('output_tokens', 0)
-        return len(tokenizer.encode(text))
+
+    def _stream(
+            self,
+            messages: List[BaseMessage],
+            stop: Optional[List[str]] = None,
+            run_manager: Optional[CallbackManagerForLLMRun] = None,
+            *,
+            tools: Optional[Sequence[Union[ToolDict, GoogleTool]]] = None,
+            functions: Optional[Sequence[FunctionDeclarationType]] = None,
+            safety_settings: Optional[SafetySettingDict] = None,
+            tool_config: Optional[Union[Dict, _ToolConfigDict]] = None,
+            generation_config: Optional[Dict[str, Any]] = None,
+            **kwargs: Any,
+    ) -> Iterator[ChatGenerationChunk]:
+        request = self._prepare_request(
+            messages,
+            stop=stop,
+            tools=tools,
+            functions=functions,
+            safety_settings=safety_settings,
+            tool_config=tool_config,
+            generation_config=generation_config,
+        )
+        response: GenerateContentResponse = _chat_with_retry(
+            request=request,
+            generation_method=self.client.stream_generate_content,
+            **kwargs,
+            metadata=self.default_metadata,
+        )
+        for chunk in response:
+            _chat_result = _response_to_result(chunk, stream=True)
+            gen = cast(ChatGenerationChunk, _chat_result.generations[0])
+            if gen.message:
+                token_usage = gen.message.usage_metadata
+                self.__dict__.setdefault('_last_generation_info', {}).update(token_usage)
+            if run_manager:
+                run_manager.on_llm_new_token(gen.text)
+            yield gen